{"title":"IFRS 9 Compliant Economic Adjustment of Expected Credit Loss Modeling","authors":"Mariya Gubareva","doi":"10.21314/jcr.2020.260","DOIUrl":null,"url":null,"abstract":"This paper presents an International Financial Reporting Standard 9 (IFRS 9) compliant solution related to expected credit loss modeling. Commonly, credit default swap(CDS) spreads are considered as market indicators of future debt performance. However, we demonstrate empirically that nondefault risks explain a relevant part of the CDS spread, and we assess the average weight-of-default component for each point in the CDS spread term structure. Thus, to be used for probability of default estimations, CDS spreads must be adjusted for the nondefault component to guarantee the neutral character of expected credit loss estimations, as required by IFRS 9. Our study introduces an innovative methodology for extracting the pure default component and probability of default calibration. To enable economic adjustment of probabilities of default we analyze the relationship between a long-run average of the across-the-sample mean CDS spread of the homogeneous cohort of issuers and the spread implied by the long-run average of the observed default rates. Our easy-to-implement solution is applied to a sample of investment-grade and high yield corporate debt issuers. We exploit differences in the economic performance of North American and euro zone obligors. The proposed framework allows us to understand complex interactions between the forward-looking impairment provisions and economic capital requirements in relation to credit losses.","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"25 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2018-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Credit Risk","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21314/jcr.2020.260","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents an International Financial Reporting Standard 9 (IFRS 9) compliant solution related to expected credit loss modeling. Commonly, credit default swap(CDS) spreads are considered as market indicators of future debt performance. However, we demonstrate empirically that nondefault risks explain a relevant part of the CDS spread, and we assess the average weight-of-default component for each point in the CDS spread term structure. Thus, to be used for probability of default estimations, CDS spreads must be adjusted for the nondefault component to guarantee the neutral character of expected credit loss estimations, as required by IFRS 9. Our study introduces an innovative methodology for extracting the pure default component and probability of default calibration. To enable economic adjustment of probabilities of default we analyze the relationship between a long-run average of the across-the-sample mean CDS spread of the homogeneous cohort of issuers and the spread implied by the long-run average of the observed default rates. Our easy-to-implement solution is applied to a sample of investment-grade and high yield corporate debt issuers. We exploit differences in the economic performance of North American and euro zone obligors. The proposed framework allows us to understand complex interactions between the forward-looking impairment provisions and economic capital requirements in relation to credit losses.
期刊介绍:
With the re-writing of the Basel accords in international banking and their ensuing application, interest in credit risk has never been greater. The Journal of Credit Risk focuses on the measurement and management of credit risk, the valuation and hedging of credit products, and aims to promote a greater understanding in the area of credit risk theory and practice. The Journal of Credit Risk considers submissions in the form of research papers and technical papers, on topics including, but not limited to: Modelling and management of portfolio credit risk Recent advances in parameterizing credit risk models: default probability estimation, copulas and credit risk correlation, recoveries and loss given default, collateral valuation, loss distributions and extreme events Pricing and hedging of credit derivatives Structured credit products and securitizations e.g. collateralized debt obligations, synthetic securitizations, credit baskets, etc. Measuring managing and hedging counterparty credit risk Credit risk transfer techniques Liquidity risk and extreme credit events Regulatory issues, such as Basel II, internal ratings systems, credit-scoring techniques and credit risk capital adequacy.